Results 51 to 60 of about 8,013,557 (321)

Dimensionality reduction reveals fine-scale structure in the Japanese population with consequences for polygenic risk prediction

Nature Communications, 2020
The diversity in our genome is crucial to understanding the demographic history of worldwide populations. However, we have yet to know whether subtle genetic differences within a population can be disentangled, or whether they have an impact on complex ...
S. Sakaue, Jun Hirata, M. Kanai, Ken Suzuki, M. Akiyama, Chun Lai Too, T. Arayssi, M. Hammoudeh, Samar Al Emadi, B. Masri, H. Halabi, H. Badsha, I. Uthman, R. Saxena, L. Padyukov, M. Hirata, K. Matsuda, Y. Murakami, Y. Kamatani, Y. Okada   +19 more
semanticscholar   +1 more source

Arabic L2 readability assessment: Dimensionality reduction study

Journal of King Saud University: Computer and Information Sciences, 2022
Readability is a measure that associates a written text to a reader’s skill or grade level. Readability assessment is very important in the field of second or foreign language (L2) learning.
Naoual Nassiri, Abdelhak Lakhouaja, Violetta Cavalli-Sforza   +2 more
doaj   +1 more source

Context-aware dimensionality reduction deconvolutes gut microbial community dynamics

Nature Biotechnology, 2020
The translational power of human microbiome studies is limited by high interindividual variation. We describe a dimensionality reduction tool, compositional tensor factorization (CTF), that incorporates information from the same host across multiple ...
C. Martino, Liat Shenhav, C. Marotz, George Armstrong, Daniel McDonald, Y. Vázquez-Baeza, James T. Morton, Lingjing Jiang, M. Dominguez-Bello, Austin D. Swafford, E. Halperin, R. Knight   +11 more
semanticscholar   +1 more source

NDDR-CNN: Layerwise Feature Fusing in Multi-Task CNNs by Neural Discriminative Dimensionality Reduction [PDF]

Computer Vision and Pattern Recognition, 2018
In this paper, we propose a novel Convolutional Neural Network (CNN) structure for general-purpose multi-task learning (MTL), which enables automatic feature fusing at every layer from different tasks.
Yuan Gao, Qi She, Jiayi Ma, Mingbo Zhao, W. Liu, A. Yuille   +5 more
semanticscholar   +1 more source

Quantum resonant dimensionality reduction

Physical Review Research
Quantum computing is a promising candidate for accelerating machine learning tasks. Limited by the control accuracy of current quantum hardware, reducing the consumption of quantum resources is the key to achieving quantum advantage.
Fan Yang, Furong Wang, Xusheng Xu, Pan Gao, Tao Xin, ShiJie Wei, Guilu Long   +6 more
doaj   +1 more source

Dimensionality reduction in data from LASER applications [PDF]

مجلة جامعة الانبار للعلوم الصرفة, 2012
Redundant variables not only in LASER applications, but in all experimental works are disturbing statistical analysis as a result of highly correlation among them.
Imad H.Aboud, Qassim M. Jameel
doaj   +1 more source

Revealing the structure of land plant photosystem II: the journey from negative‐stain EM to cryo‐EM

FEBS Letters, EarlyView.
Advances in cryo‐EM have revealed the detailed structure of Photosystem II, a key protein complex driving photosynthesis. This review traces the journey from early low‐resolution images to high‐resolution models, highlighting how these discoveries deepen our understanding of light harvesting and energy conversion in plants.
Roman Kouřil
wiley   +1 more source

Linear Dimensionality Reduction: What Is Better?

Data
This research paper focuses on dimensionality reduction, which is a major subproblem in any data processing operation. Dimensionality reduction based on principal components is the most used methodology. Our paper examines three heuristics, namely Kaiser’
Mohit Baliyan, Evgeny M. Mirkes
doaj   +1 more source

Organoids in pediatric cancer research

FEBS Letters, EarlyView.
Organoid technology has revolutionized cancer research, yet its application in pediatric oncology remains limited. Recent advances have enabled the development of pediatric tumor organoids, offering new insights into disease biology, treatment response, and interactions with the tumor microenvironment.
Carla Ríos Arceo, Jarno Drost
wiley   +1 more source

Dimensionality reduction method for hyperspectral image analysis based on rough set theory

European Journal of Remote Sensing, 2020
High-dimensional features often cause computational complexity and dimensionality curse. Feature selection and feature extraction are the two mainstream methods for dimensionality reduction.
Zhenhua Wang, Suling Liang, Lizhi Xu, Wei Song, Dexing Wang, Dongmei Huang   +5 more
doaj   +1 more source